The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
In real life, background noise contaminates pure voice and degrades the performance and capabilities of voice communication systems such as mobile phones, voice recognition, voice coding, speaker recognition and the like. Accordingly, research on sound quality improvement to reduce noise effects and enhance system capabilities has progressed over time, and the importance thereof currently receives a lot of attention.
Meanwhile, a Spectral Subtraction (SS) is a typical method widely used in a single channel due to its low cost and easy implementation among various sound quality improving methods. The inventors have noted that in the spectral subtraction there might remain musical noise corresponding to a new artifact sound in the voice signals even after the spectral subtraction.
The musical noise refers to a random frequency component generated by evaluating estimated noise as being lower than original noise, and furthermore refers to a tone which perceivedly annoys a listener since residue of the musical noise on time and frequency axes in a spectrogram is discontinuously spread.
In this connection, in order to suppress the residue of the musical noise, the spectral subtraction method based on a gain function has been proposed.
For example, there are “wiener filtering”, “nonlinear spectral subtraction with oversubtraction factor and spectral floor”, “minimum mean square error short-time spectral amplitude estimation or log spectral amplitude”, “oversubtraction based on masking properties of human auditory system”, and “soft decision estimation, maximum likelihood, signal subspace”. The inventors have noted that most of the proposed methods might not be able to efficiently improve sound quality in a noise environment having a low Signal to Noise Ratio (SNR).
In other words, the inventors have noted that when noise estimated to be larger than the actual noise and an over-evaluated gain function are used, the residue and divergence of the musical noise are reduced, but voice distortion increases. The inventors have noted that, inversely, when noise estimated to be lower than the actual noise and an under-evaluated gain function are used, voice distortion is reduced but the residue and divergence of the musical noise increases.